How many leaves should a tree grow? This information is critical to climate models as the amount of leaf area per unit ground area, or leaf area index (LAI), helps determines the exchange of carbon (photosynthesis, respiration) and water (evapotranspiration) fluxes between the vegetation and the atmosphere.

However, modelling LAI and how it changes can be difficult. Several recent model comparisons have shown that large disagreements among models and compared to satellite-based estimates. This occurs because simulated LAI is the result of a series of different model assumptions: how much carbon do plants use to grow leaves, how long do these leaves grow for, how does drought affect the growth of leaves, etc.

Researchers at Western Sydney University, in collaboration with a CLEX researcher, tested an alternative approach to determine continental-scale LAI. Returning to the question of how many leaves a tree should grow – in water limited ecosystems (i.e. Australia) there is a long-standing hypothesis (dating back to the 1980s), that the LAI is dictated by the long-term water availability.

The researchers used long-term climate data to test this hypothesis, allowing plants to adjust their long-term LAI and stomatal behaviour to maximise carbon gain under the constraint of water availability over time. Using this ecohydrological theory they made predictions of “equilibrium” LAI across Australia, comparing results against satellite-derived estimates.

The results showed a high level of consistency between their model predictions and ground- and satellite-based measurements.

They also made predictions about how LAI should have changed with recent (1980-2010) changes in atmospheric carbon dioxide concentrations. These predicted changes were also consistent with changes in satellite-based estimates.

This research clearly demonstrates the potential to predict long-term LAI using simple ecohydrological theory. This approach could potentially be incorporated into existing terrestrial biosphere models and help improve predictions of LAI.